Hi,
I have never used numpy in my python applications until now. I am writing a python/openGL based tool to manipulate 3d geometrical data(meshes, curve, points etc.) I would be using numpy to store these objects(vertices, edges, faces, index etc.) at run time. One of my major concern is numpy's file IO capabilities. Geometrical objects would be stored in a structures, for example a logical structure to store a mesh goes like this:
struct(
name(string)
vertex(numpy.float16)[x, y, z]
normal(numpy.float16)[x, y, z]
edges(numpy.int)
st(2d numpy.float16)[u, v]
index(numpy.int)
)
There would be different structures for curve, patch, points and rest of the primitives. I am sure numpy users must have encounered similar scenerio where
you need to dump this data to a file and read it back. In my case, a general assumption of nearly 50-150 megs of data would be considered as normal size.
Before I go deep into coding It would be great if numpy user can share their expreience for the task.
I am also open for unconventional or off the route methods, provided they can do the job.(C/c++, 3rd party modules etc.)
Here is the summery of IO operations I would be working on:
1. Write different structures to a file.
2. Read data back from file.
3. if structure can be tagged(int or string) then read a particular structure using tag, from file.
Hope to here from numpy users soon :-)
Regards
Prashant
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